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  1. README.md +51 -3
  2. config.json +20 -0
  3. fill-mask-result.png +0 -0
  4. gitattributes +28 -0
  5. model.safetensors +3 -0
  6. pytorch_model.bin +3 -0
  7. vocab.txt +0 -0
README.md CHANGED
@@ -1,3 +1,51 @@
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- ---
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- license: mit
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language: en
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+ thumbnail: https://github.com/jackaduma
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+ tags:
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+ - exbert
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+ - security
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+ - cybersecurity
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+ - cyber security
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+ - threat hunting
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+ - threat intelligence
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+ license: apache-2.0
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+ datasets:
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+ - APTnotes
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+ - Stucco-Data
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+ - CASIE
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+ ---
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+
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+
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+ # SecBERT
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+
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+ This is the pretrained model presented in [SecBERT: A Pretrained Language Model for Cyber Security Text](https://github.com/jackaduma/SecBERT/), which is a BERT model trained on cyber security text.
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+
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+ The training corpus was papers taken from
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+ * [APTnotes](https://github.com/kbandla/APTnotes)
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+ * [Stucco-Data: Cyber security data sources](https://stucco.github.io/data/)
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+ * [CASIE: Extracting Cybersecurity Event Information from Text](https://ebiquity.umbc.edu/_file_directory_/papers/943.pdf)
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+ * [SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)](https://competitions.codalab.org/competitions/17262).
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+
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+ SecBERT has its own wordpiece vocabulary (secvocab) that's built to best match the training corpus.
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+
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+ We trained [SecBERT](https://huggingface.co/jackaduma/SecBERT) and [SecRoBERTa](https://huggingface.co/jackaduma/SecRoBERTa) versions.
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+
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+ Available models include:
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+ * [`SecBERT`](https://huggingface.co/jackaduma/SecBERT)
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+ * [`SecRoBERTa`](https://huggingface.co/jackaduma/SecRoBERTa)
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+
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+ ---
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+ ## **Fill Mask**
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+
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+ We proposed to build language model which work on cyber security text, as result, it can improve downstream tasks (NER, Text Classification, Semantic Understand, Q&A) in Cyber Security Domain.
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+ First, as below shows Fill-Mask pipeline in [Google Bert](), [AllenAI SciBert](https://github.com/allenai/scibert) and our [SecBERT](https://github.com/jackaduma/SecBERT) .
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+
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+
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+ <!-- <img src="./fill-mask-result.png" width="150%" height="150%"> -->
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+
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+ ![fill-mask-result](https://github.com/jackaduma/SecBERT/blob/main/fill-mask-result.png?raw=true)
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+
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+ ---
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+
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+ The original repo can be found [here](https://github.com/jackaduma/SecBERT).
config.json ADDED
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+ {
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+ "architectures": [
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+ "BertForMaskedLM"
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+ "attention_probs_dropout_prob": 0.1,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 514,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pad_token_id": 0,
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+ "type_vocab_size": 1,
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+ "vocab_size": 52000
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+ }
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